Back in 2008, one of my
friends had the following conversation with me in a BBQ party:
"So you work in an
IT company, what specific area?" He asked.
"BI - Business
Intelligence" I said.
"That sounds pretty
cool. Do you spend a lot of time with things like Robots?" He asked again.
...
According to
Merriam-Webster Dictionary, the definition of "Intelligence" is
A) The ability to learn
or understand or to deal with new or trying situations: REASON: also: the
skilled use of reason
Or
B) News or information
concerning an enemy or possible enemy or an area; also : an agency engaged in
obtaining such information.
In BI, the letter
"I" means "Intelligence" as of "Central Intelligence
Agency", but not "Intelligence" as of "Artificial
Intelligence". Therefore, the definition of Business Intelligence can be
simply put as "getting information of Business for having a better
business". Logically, a few questions will rise: What information do I
need to collect? How should I manage the information? In which ways I can
digest the information?
Information
Asset
|
Here comes the second
set of questions: How do I collect the information? How do I manage the
information so that it can give business insight to the end users? The answer
in my mind is ETL (data Extraction, Transformation and Loading) and DW (Data
Warehouse). It's not unusual that one business has data scattered in
multiple heterogeneous data storage. With a proper ETL tool,
data from different sources can be extracted, transformed accordingly and
loaded into the repository for analysis purpose. A mature ERP or CRM
system is normally the major source for ETL process as it records the most
detail operational business activities such as transaction closed, customer
acquired, product manufactured, etc. In addition, other complementary
information such as Excel files exchanged between people, small Access
databases created and managed by line of business, old but relevant data stored
in legacy systems, may also need to be processed via ETL, so that a
comprehensive intelligence storage can be build to cater for all kinds of
business questions. The destination of ETL process is normally a data warehouse
(or several data marts which is data warehouse with smaller controlled scope).
Data Warehouse is the foundation of Business Intelligence. Unlike
OLTP system which needs to insert/update/delete data in timely fashion, Data
Warehouse needs to be optimized for performing data queries. Consequently, data
in Data Warehouse is saved in denormalized form of database schemas. Typical
database denormalization techniques include but not limited to: materialized
views, star schemas or OLAP cubes. Each approach has its pros and cons but they
all share the same objectives: speed up the query of business measures (e.g.
sales revenue, call duration) by different business dimensions (e.g. time,
location, line of business).
So far, we've discussed
two aspects: where is the information coming from, how to collect and stored it
so that it can be ready for business questions. Now, let's have a look at the
last one: With a Business Intelligence system, how can the business operators
find and digest information effectively and efficiently? As far as I
understand, a competent BI system should be able to expose information
through three basic channels: periodic operational
report, interactive dashboard, and ad-hoc analysis. Operational
reporting is the entry level part of Business Intelligence.
It periodically provides the updated snapshots of business from
different aspects. Operational reporting normally consists of a set of
pre-defined (both data query and layout) reports such as weekly inventory
report, monthly salary expenditure report and so on. It helps people to record
and monitor what happened with the business. Interactive dashboard is the way
how variant reports can be organized together on one screen display.
Without scrolling or switching the display, user should be able to
see multiple related reports at a glance. For example, a typical
Financial Profitability analysis dashboard may have reports such as P&L
Summary, Cost Breakdown, Product Gross Margin and Customer Gross Margin on one
single page. In addition, Interactions such as filtering, drilling, layout
personalization should also be available for users. With Interactive dashboard,
people can focus on interested information in different forms, slice and dice,
drill and filter to get a deeper business insight. Ad-hoc analysis means
analyze data in a exploratory self-service approach. Business users
should be able to find answers to their questions by defining criteria,
customizing calculation formula, specifying conditional formatting and so on in
a friendly graphical interface. When it's necessary, a BI environment should
also allow users to quickly create tabulate or graphical reports
from arbitrary data sources without going through a formal data
modeling process. Ad-hoc analysis empowers business users to find answers
to the specific questions which are not covered by canned dashboards and
reports. Besides these three major intelligence delivery channels, a
mature BI system will also provide Proactive alerting, Office integration,
Mobile capability, etc.
Delivery
Channels
|
In summary, Business
Intelligence is a platform that helps people to collect, manage and convey
information. By turning big volume of multifarious data into sensible abstract
intelligence, BI helps people make business decisions in a more efficient and accurate
way.
In my future blog
entries, I will share with you what I've learnt about general Business
Intelligence and Oracle Business Intelligence solution.
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